Map

Presented up front is the final product for which the rest of this document describes. It is a map of the ORMGP jurisdiction discretized into ~10km² sub-watersheds. Clicking at any sub-watershed will return a number of properties. In the figure below, sub-watersheds are colour-coded according to their degree of impervious cover. # {r, echo=FALSE, message=FALSE, warning=FALSE, out.height='600px', out.width='100%', fig.cap="ORMGP v.2020 10km² sub-watershed map. Click a subwatershed to view spatial properties."} # library(leaflet) # library(rgdal) # ormgp <- readOGR("shp/owrc20-50a_SWS10-final.geojson",verbose = FALSE) # # leaflet(ormgp) %>% # addProviderTiles( providers$Stamen.TonerLite, options = providerTileOptions(noWrap = TRUE) ) %>% # addPolygons(color = ~colorQuantile("YlGnBu", ormgp$perimp)(perimp), # popup = ~paste0('<b>sub-watershed: ',mmID,'</b>', # '<br> area: ',round(Area/1000000,1),'km²', # '<br> permeability: ',perm, # '<br> impervious cover: ',round(perimp*100,0),'%', # '<br> canopy cover: ',round(percov*100,0),'%', # '<br> open water cover: ',round(perow*100,0),'%', # '<br> wetland cover: ',round(perwl*100,0),'%' # ) # ) # #

Introduction

The 3 million hectare ORMGP jurisdiction is subdivided to a number of 10km² sub-watersheds as a basis for hydrometeorological data analysis. Every sub-watershed has a defined topological order in which headwater sub-watersheds can easily be mapped to subsequent downstream sub-watersheds, and so on until feeding the great lakes. The intent here is to deem these sub-watersheds a “logical unit” for climatological and water budget analyses. Below is a description of the derivation the v.2020 OWRC 10km² sub-watershed map and its derivatives including:

  • a catchment area delineation tool
  • an interpolated real-time daily meteorological dataset dating back to the year 1900
  • an overlay analysis performed to characterize sub-watershed:
  • impervious area
  • canopy coverage
  • water body coverage
  • wetland coverage
  • relative permeability/infiltrability
  • mean slope and dominant aspect
  • mean depth to water table.

Below first describes the processing of a Provincial Digital Elevation Model (DEM) yielding a “hydrologically-correct” model of the ORMGP ground surface. From this information, the ORMGP region is portioned into 2,813 ~10km² sub-watersheds.

Next, the hydrologically-corrected digital elevation model (HDEM) is further process to derive a number of metrics aggregated at the sub-watershed scale.

Digital Elevation Model

Ground surface elevations were collected from the 2006 version of the Provincial (Ministry of Natural Resources) Digital Elevation Model (DEM). This is a 10x10m² DEM derived from 1:10,000 scale OBM base mapping based on photogrammetic elevation points and 5m contours where the photogrammetic elevation points did not exist. An up-scaled 50x50m² Digital Elevation Model (DEM) is produced by merging the tiles shown below:

MNR 2006 Provincial DEM tiles shown in green.

MNR 2006 Provincial DEM tiles shown in green.

Elevation data were up-scaled by taking the average of known elevations occurring within every 50x50m² cell. The resulting grid is a 5000x5000 50m-uniform cell grid, with an upper-left-corner origin at (E: 545,000, N: 5,035,000) NAD83 UTM zone 17.

Hydrological “correction”

An automated topological topological analysis is performed on the DEM using the following methodologies:

  1. Automated depression filling (Wang and Liu, 2006) was applied to the DEM. This filtering of elevation data ensures that every grid cell has at least 1 neighbouring cell with an assiged elevation at or below the current cell’s elevation. This ensures that “drainage” is never impeded.
  2. While the above code works for most of the area, it will leave flat (zero-gradient) regions especially around lakes and wetlands. A fix by Garbrecht and Martz (1997) was added to ensure a consistent flow direction with negligeable change to the corrected DEM.
  3. Flowpaths are then computed based on the “D8” algorithm (O’Callaghan and Mark, 1984).

Cell slopes and aspects are computed using a 9-point planar regression from the cell’s elevation plus it’s 8 neighbouring elevations.

Manual adjustments

While automated hydrological correction is quite powerful when applied to the Provincial DEM, there are in rare places where the algorithm fails to capture mapped flow paths (usually in flatter rural regions close to embanked roads). Fortunately, these errors can be easily corrected by imposing flow directions using hand-drawn flow paths. Flow paths are save as polylines, where its vertices are ordered according to flow direction.

With the current version (v.2020), 10 flow corrections have been imposed and are saved in a set of shapefiles. There is at the moment 1 new flow path correction in queue and will be imposed for the next release. This is to say that this layer and its derivatives are continually being updated.

Validation

ORMGP regional 50x50m² Hydrologically corrected Digital Elevation Model (HDEM) The ORMGP regional 50x50m² Hydrologically corrected Digital Elevation Model (HDEM, v.2020)

{#fig.hdem}


The benefit of computing the flow direction topology associated with the HDEM is that any user a could place a “virual particle” on the landscape and follow its drainage path as it traverses toward its terminous; in this case, the Great Lakes.

More importantly however, given an HDEM, one can also efficiently compute the contributing area to any selected point on the landscape. (A live demonstration of this is presented below.) This feature provides the means to validate the procesessing presented in this document.

Locations of 96 current and historical stream flow gauges are used to compare drainage areas reported to the drainage areas computed using the HDEM. Sources of the station locations were collected from the Water Survey of Canada and the Toronto Region Conservation Authority. The table below lists the stations used, followed by a figure comparing their match to the HDEM. As mentionned earlier, this layer will continually be updated with input from users and it is expected that this validation can only improve.


List of streamflow gauging stations with reported contributing area.
Contributing Area
Station ID Long Lat reported (km²) computed (km²) difference (%)
02EC008 -79.3 44.3 272.0 297.9 9.5
02EC009 -79.5 44.1 176.0 176.8 0.4
02EC010 -79.7 44.0 51.3 44.0 -14.3
02EC011 -79.1 44.4 291.0 292.4 0.5
02EC018 -79.2 44.3 347.0 336.2 -3.1
02ED007 -79.6 44.7 168.0 183.5 9.2
02ED013 -79.9 44.6 121.0 121.3 0.2
02ED014 -80.0 44.2 190.0 181.4 -4.5
02ED015 -80.1 44.3 244.0 253.4 3.9
02ED017 -79.8 44.7 65.2 58.5 -10.3
02ED024 -79.6 44.8 244.0 243.2 -0.3
02ED026 -80.0 44.0 176.0 177.2 0.7
02ED029 -79.8 44.1 479.0 479.8 0.2
02ED100 -79.8 44.0 86.0 75.0 -12.8
02ED101 -79.9 44.1 328.0 328.9 0.3
02ED102 -79.9 44.2 216.0 218.9 1.4
02GA014 -80.3 43.9 663.0 597.3 -9.9
02GA015 -80.3 43.5 567.9 573.2 0.9
02GA016 -80.3 43.7 784.8 719.6 -8.3
02GA029 -80.2 43.5 231.0 242.5 5.0
02GA031 -80.1 43.6 41.5 44.1 6.4
02GA040 -80.3 43.6 167.0 170.1 1.8
02GA041 -80.4 44.1 66.5 66.3 -0.3
02HB001 -80.0 43.8 208.8 202.5 -3.0
02HB004 -79.8 43.5 193.0 194.9 1.0
02HB005 -79.9 43.5 101.3 105.0 3.6
02HB008 -79.9 43.6 131.0 127.4 -2.7
02HB011 -79.9 43.4 242.0 243.0 0.4
02HB013 -80.1 43.9 60.6 59.9 -1.2
02HB015 -80.1 43.4 63.5 54.2 -14.6
02HB018 -79.9 43.8 414.7 409.3 -1.3
02HB020 -80.1 43.8 32.3 32.9 1.9
02HB022 -80.0 43.4 123.4 117.7 -4.6
02HB024 -80.0 43.6 18.9 20.2 6.8
02HB025 -79.9 43.6 644.8 639.6 -0.8
02HB027 -79.7 43.4 24.5 25.8 5.4
02HC003 -79.5 43.7 802.0 805.6 0.4
02HC005 -79.4 43.7 88.1 89.2 1.2
02HC009 -79.6 43.8 190.9 189.8 -0.6
02HC013 -79.2 43.8 89.1 89.0 -0.1
02HC017 -79.8 43.7 68.6 62.7 -8.6
02HC018 -79.0 43.9 100.3 99.8 -0.5
02HC019 -79.1 43.9 93.5 86.9 -7.0
02HC022 -79.2 43.9 181.3 178.9 -1.3
02HC023 -79.7 43.9 62.2 63.4 1.9
02HC024 -79.4 43.7 318.5 322.6 1.3
02HC025 -79.6 43.8 296.3 300.0 1.2
02HC027 -79.5 43.7 58.0 65.9 13.6
02HC028 -79.2 43.9 83.6 62.4 -25.3
02HC030 -79.6 43.6 205.0 181.1 -11.6
02HC031 -79.7 43.8 142.2 141.0 -0.9
02HC032 -79.6 43.9 94.8 91.9 -3.1
02HC033 -79.5 43.6 67.8 67.9 0.2
02HC038 -79.2 43.9 52.0 62.4 20.1
02HC047 -79.8 43.9 163.5 167.6 2.5
02HC049 -79.1 43.8 257.5 257.1 -0.2
02HC051 -79.8 43.9 42.0 41.1 -2.1
02HC053 -79.3 43.9 59.0 59.3 0.5
02HC054 -79.0 44.0 39.0 38.9 -0.3
02HC055 -79.0 43.9 37.6 37.6 -0.1
02HD003 -78.4 44.0 67.3 72.9 8.3
02HD004 -78.4 44.0 46.1 40.1 -13.1
02HD006 -78.7 43.9 80.9 78.4 -3.2
02HD008 -78.9 43.9 95.8 95.8 0.0
02HD009 -78.6 43.9 80.7 81.0 0.3
02HD010 -78.0 44.0 63.8 63.4 -0.6
02HD012 -78.3 44.0 241.9 239.9 -0.8
02HD013 -78.8 43.9 42.9 42.9 0.2
02HD018 -77.7 44.1 16.8 16.3 -2.9
02HD019 -78.2 44.0 122.1 122.7 0.5
02HG002 -79.0 44.1 32.6 41.4 26.8
02HJ001 -78.3 44.3 116.2 116.2 0.1
02HJ003 -78.0 44.3 282.6 281.6 -0.4
02HJ005 -78.4 44.1 11.6 11.6 0.1
02HK005 -77.9 44.8 456.0 440.5 -3.4
02HK006 -77.7 44.5 552.8 528.9 -4.3
02HK007 -77.8 44.1 160.5 160.8 0.2
02HK008 -77.5 44.3 93.0 90.4 -2.8
02HK009 -77.9 44.2 82.6 79.7 -3.5
02HK011 -77.6 44.1 33.0 32.7 -1.0
02HL003 -77.4 44.5 429.0 424.8 -1.0
02HL005 -77.6 44.5 296.9 294.6 -0.8
02KD002 -77.8 45.1 844.5 789.4 -6.5
HY010 -79.1 43.9 15.1 15.1 0.0
HY023 -79.1 43.9 62.1 62.1 0.0
HY024 -79.7 43.7 81.5 81.5 0.0
HY028 -79.1 43.9 11.3 11.3 0.0
HY034 -79.2 43.8 11.8 11.8 0.0
HY040 -79.1 43.8 2.7 2.7 0.0
HY045 -79.6 43.7 38.4 38.4 0.0
HY047 -79.1 44.0 23.1 23.1 0.0
HY051 -79.1 43.8 25.7 25.7 0.0
HY052 -79.1 43.8 8.0 8.0 0.0
HY059 -79.7 43.7 36.9 36.9 0.0
HY065 -79.1 43.9 13.7 13.7 0.0
HY082 -79.2 43.9 34.4 34.4 0.0

Derivative products

An overlay analysis is the process of overlaying 2 or more spatial layers and capturing statistics associated with their relative coverage. In this case, the sub-watershed layer is overlain by Provincial land-use and surficial geology layers to obtain information like percent impervious, relative permeability, etc.

Provincial layers discussed in more detail below have in all cases been re-sampled to the 50x50m² grid associated with the hydrologically corrected DEM. It is from these rasters where the aggregation of watershed characteristics is computed.

Land use

The Ministry of Natural Resources and Forestry (2019) SOLRIS version 3.0 provincial land use layer is employed to aggregate imperviousness and canopy coverage at the sub-watershed scale. In areas to the north, where the SOLRIS coverage discontinues, interpretation was applied by:

  1. Using Provincial mapping of roads, wetlands and water bodies, areas outside of the SOLRIS data bounds (typically up on the Canadian Shield) are filled in with the appropriate SOLRIS land use class index (201, 150, 170, respectively–MNRF, 2019); and,
  2. All remaining area not covered by SOLRIS is assumed Forest (SOLRIS land use class index of 90), as observed with satellite imagery.

The dominant SOLRIS land use class (by area) is assigned the Land use class index for every 50x50m² grid cell.

Final 50x50m SOLRIS mapping. Final 50x50m SOLRIS mapping. (For illustrative purposes only see here to reproduce shown raster.)


Land use coverage

For any ~10km² sub-watershed and give a 50x50m² grid , there should be a set of roughly 4,000 SOLRIS land use class indices. Using a look-up system, the set of cells contained within a sub-watershed are assigned a value of imperviousness, water body, wetland and canopy coverage (according to their SOLRIS index) and accumulated to a sub-watershed sum.


Percent impervious and canopy coverage as per SOLRIS v3.0 (MNRF, 2019) land use classification.
SOLRIS Land use classification
Index Name Imperviousness (%) Canopy cover (%)
11 Open Beach/Bar
21 Open Sand Dune
23 Treed Sand Dune 50
41 Open Cliff and Talus
43 Treed Cliff and Talus 50
51 Open Alvar
52 Shrub Alvar 25
53 Treed Alvar 50
64 Open Bedrock
65 Sparse Treed 40
81 Open Tallgrass Prairie 10
82 Tallgrass Savannah 35
83 Tallgrass Woodland 85
90 Forest 100
91 Coniferous Forest 100
92 Mixed Forest 100
93 Deciduous Forest 100
131 Treed Swamp 50
135 Thicket Swamp 50
140 Fen 25
150 Bog 25
160 Marsh 25
170 Open Water
191 Plantations – Tree Cultivated 85
192 Hedge Rows 85
193 Tilled
201 Transportation 85
202 Built-Up Area– Pervious 10 10
203 Built-Up Area– Impervious 90
204 Extraction–Aggregate
205 Extraction –Peat/Topsoil 10
250 Undifferentiated


Final 50x50m impervious mapping. (For illustrative purposes only see here to reproduce shown raster.)

Final 50x50m canopy mapping. Final 50x50m canopy mapping. (For illustrative purposes only see here to reproduce shown raster.)


Surficial geology

The Ontario Geological Survey’s 2010 Surficial geology of southern Ontario layer also assigns a 50x50m² grid by the dominant class.

Final 50x50m permeability mapping. Final 50x50m permeability mapping. (For illustrative purposes only see here to reproduce shown raster.)


Permeability

The OGS classes have been grouped according to the attribute “permeability” using a similar look-up table cross-referencing scheme. OGS (2010) adds: “Permeability classification is a very generalized one, based purely on characteristics of material types.”

After assigning an assumed “effective” hydraulic conductivity to every permeability group, sub-watershed “permeability” is then calculated as the geometric mean of 50x50m² grid cells contained within a sub-watershed. Effective hydraulic conductivity value assumed for every permeability group is shown here:


Permeability classifications (after OGS, 2010) and assumed effective hydraulic conductivities.
K (m/s)
Low 1e-09
Low-medium 1e-08
Medium 1e-07
Medium-high 1e-06
high 1e-05
unknown/variable 1e-08
fluvial 1e-05
organics 1e-06

The resulting effective hydraulic conductivity is then reverted back to the nearest Low–High OGS (2010) classification.

Contributing area delineation

One (of many) APIs (application programming interfaces) hosted by the ORMGP leverages the drainage topology computed in the area. Now, users have the ability to have returned a delineated catchment area polygon for any given point that lies within the HDEM extent. Try below:

ORMGP v.2020 HDEM. Click anywhere (within our jurisdiction) to return its contributing area.

Source code

Processing discussed above has been documented using a jupyter notebook. Source data can be found here and additional outputs can be found here.

References

Garbrecht Martz 1997 The assignment of drainage direction over flat surfaces in raster digital elevation models

O’Callaghan, J.F., and D.M. Mark, 1984. The extraction of drainage net-works from digital elevation data, Comput. Vision Graphics Image Process., 28, pp. 328-344

Ontario Geological Survey 2010. Surficial geology of southern Ontario; Ontario Geological Survey, Miscellaneous Release— Data 128 – Revised.

Ministry of Natural Resources and Forestry, 2019. Southern Ontario Land Resource Information System (SOLRIS) Version 3.0: Data Specifications. Science and Research Branch, April 2019

Wang, L., H. Liu, 2006. An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling. International Journal of Geographical Information Science 20(2): 193-213.